In the field of content matching and recommendation, Recommender systems are active information filtering systems that attempt to present to the user information items (film, television, music, books, news, web pages) the user is interested in. These systems add or remove information items to the information flowing towards the user. Recommender systems typically use collaborative filtering approaches or a combination of the collaborative filtering and content-based filtering approaches.
Taking the above into account, there clearly remains a need, in the fields of content matching and recommendation, for systems apparatuses circuits methods and associated computer executable code sets that introduce unique approaches to content recommendation, adapted to match the tastes and preferences of not a single user but rather a group of users, based on their various preferences and taste profiles.